Audio processing, Image processing

Network routing

Data compression

Text processing

Analog signals are continuous and vary in amplitude or frequency; digital signals are discrete and represent data in binary form.

Analog signals use binary code; digital signals use waveforms.

Analog signals are always digital; digital signals are continuous.

Digital signals vary in amplitude; analog signals are discrete.

Sampling is the process of converting a continuous-time signal into a discrete-time signal by taking periodic samples.

Sampling is the technique of merging multiple signals into one continuous signal.

Sampling is the process of amplifying a signal to increase its power.

Sampling involves filtering a signal to remove noise before processing.

The Nyquist theorem describes the maximum frequency of a signal that can be transmitted without distortion.

The Nyquist theorem states that signals can be sampled at any rate without loss.

The Nyquist theorem defines the minimum sampling rate required to avoid aliasing in signal processing.

The Nyquist theorem is a principle in thermodynamics related to heat transfer.

Quantization is the process of increasing the sample rate in DSP.

Quantization refers to the compression of audio signals in DSP.

Quantization is the technique of filtering noise from signals in DSP.

Quantization is the process of mapping continuous values to discrete values in DSP.

A continuous-time signal is a series of values at random time points.

A discrete-time signal is a sequence of values representing a signal at distinct time intervals.

A discrete-time signal is a single value measured at one time.

A discrete-time signal is a waveform that varies continuously over time.

FFT is primarily for data storage in DSP.

FFT helps in generating random signals in DSP.

FFT is used for image compression in DSP.

FFT enables efficient frequency analysis and manipulation of signals in DSP.

Filtering is the process of modifying or enhancing a signal by removing unwanted components or extracting desired features.

Filtering is the process of amplifying all signal components equally.

Filtering is the technique of adding noise to a signal for analysis.

Filtering refers to the conversion of analog signals to digital format.

Windowing is used to increase noise in signal analysis.

Windowing has no effect on frequency representation.

Windowing is important in signal analysis to reduce spectral leakage and improve frequency representation.

Windowing is only important for visualizing signals, not for analysis.